Abstracting Soft Constraints: Some Experimental Results on Fuzzy CSPs

ing Soft Constraints: Some Experimental Results on Fuzzy CSPs Stefano Bistarelli1 2, Francesca Rossi3, and Isabella Pilan3 1 Istituto di Informatica e Telematica, CNR, Pisa, Italy [email protected] 2 Dipartimento di Scienze Universitá degli Studi “G. D’annunzio” di Chieti-Pescara, Italy [email protected] 3 Dipartimento di Matematica Pura ed Applicata Università di Padova, Italy frossi,ipilan @math.unipd.it Abstract. Soft constraints are very flexible and expressive. However, they may also be very complex to handle. For this reason, it may be convenient in several cases to pass to an abstract version of a given soft problem, and then bring some useful information from the abstract problem to the concrete one. This will hopefully make the search for a solution, or for an optimal solution, of the concrete problem, faster. In this paper we review the main concepts and properties of our abstraction framework for soft constraints, and we show some experimental results of its application to the solution of fuzzy constraints. Soft constraints are very flexible and expressive. However, they may also be very complex to handle. For this reason, it may be convenient in several cases to pass to an abstract version of a given soft problem, and then bring some useful information from the abstract problem to the concrete one. This will hopefully make the search for a solution, or for an optimal solution, of the concrete problem, faster. In this paper we review the main concepts and properties of our abstraction framework for soft constraints, and we show some experimental results of its application to the solution of fuzzy constraints.